Implantable cardiac stimulation devices are now commonly used in medical practice. These devices provide periodic electrical stimulus to the heart to regulate heart function. For example, a pacemaker is generally arranged to deliver rhythmic electrical pulses to the heart to maintain a normal rhythm in patients having bradycardia or other conduction abnormalities. In addition, an implantable cardioverter defibrillator, commonly referred to as an “ICD”, can also recognize tachycardia and/or fibrillation and deliver electrical therapy to terminate such arrhythmias.
Various implantable devices, i.e. cardiac pacemakers or cardiovertors, have been developed to analyze intracardiac electrograms to diagnose the presence of conduction abnormalities as well as the presence and the evolution of various disease states in real time, so as to be able to adapt consequently the operation of the device. An intracardiac electrogram (IEGM) signal collected (i.e. sensed or detected) by electrodes coupled to one or more leads implanted in a patient's heart can be used to monitor a series of wave complexes known as the “PQRST” complexes corresponding to the succession of the cardiac beats of the patient. The QRS complex in a cardiac cycle represents the depolarization of the ventricles and is followed by a T wave which represents the repolarization of the ventricles.
The T wave (repolarization wave) amplitude and shape are quite variable, and are sensitive to conduction disturbances in the myocardium and are therefore, often used to detect and monitor the progression of various disease states such as ischemia. For example, elevation of the amplitude of the T-wave (the ST segment) is a significant indicator of cardiac electric instability of the patient. The level of amplitude elevation of the ST segment can therefore be used to detect and monitor the progression of ischemia. However, the ST segment can be affected by conditions other than ischemia, such as electrolyte imbalance, mental stress, diabetes and the like, reducing the efficacy of ST segment analysis.
Similarly, fusion beats can corrupt IEGM analysis, further reducing the efficacy of rhythm analysis and detection of disease progression. Fusion is a variable and essentially random event that results from a cardiac depolarization that originates from more than one cardiac focus, one of which is a pacing pulse and the other(s) is(are) intrinsic in origin. An algorithm that evaluates or processes signals during cardiac repolarization can be negatively affected by ‘fusion’ due to the chaotic nature of the resulting waveform that results from a fusion beat. Thus, such ‘fusion’ events should be censored from analysis, and excluded from rhythm analysis and disease state detection.